Prediction of Spontaneous Combustion Three-Zone Distribution in Gobs During the Terminal Mining Phase Based on WOA-BP Model

During the terminal mining phase of in gobs, the advancing rate slows gradually, and the distribution of spontaneous combustion three-zone in gobs undergoes significant changes, yet there remains a lack of simple and effective prediction methods. To address this issue, the oxygen concentration distribution and temperature distribution data on both intake-side and return-side at longwall advancing rates of 2 m/d, 1.2 m/d, and 0.6 m/d were obtained through on-site monitoring. A generative adversarial network was employed to learn from measured data, generating additional usable data to build the dataset. Mining status parameters, oxygen concentration distribution, and temperature distribution were extracted as input variables. Whale optimization algorithm-back propagation model was proposed, establishing nonlinear mapping relationships between advancing rate and initiation depth of oxidation zone/asphyxiation zone. The results demonstrate that (i) the WOA-BP model can effectively predict distribution of spontaneous combustion three-zone during terminal mining phase, significantly improving prediction accuracy compared with BP and AdaBoost-BP; (ii) by SHAP feature analysis, contribution of advancing rate is the highest, which can provide reliable predictive performance; (iii) the slower the advancing rate, the closer the oxidation zone and the asphyxiation zone will be to working surface. This provides a foundational direction for preventing spontaneous combustion in gobs.